1. Field of the Invention
This invention relates to image transformation by topological mapping. More particularly, this invention relates to combining a 2-dimensional medical image with a 3-dimensional map.
2. Description of the Related Art
Methods for 3-dimensional geometrical mapping and reconstruction of the endocardial surface are known in the art. For example, U.S. Pat. No. 5,738,096, whose disclosure is incorporated herein by reference, describes methods for mapping the endocardium based on bringing a probe into contact with multiple locations on a wall of the heart, and determining position coordinates of the probe at each of the locations. The position coordinates are combined to form a map of at least a portion of the heart.
Commercial electrophysiological and physical mapping systems based on detecting the position of a probe inside the body are presently available. Among them, the CARTO® 3 System, available from Biosense Webster, Inc., 3333 Diamond Canyon Road, Diamond Bar, Calif. 91765, is a system for automatic association and mapping of local electrical activity with catheter location.
In current cardiac catheterization systems, the operating physician must often observe two different images simultaneously, on two different screens: 2-dimensional fluoroscopic images of the thorax and 3-dimensional maps of the heart. Such 3-dimensional maps may be generated, for example, using magnetic tracking of the catheter tip in the heart. Both the fluoroscopic images and the 3-dimensional maps may show the catheter, but from different angles and perspectives. Because of the lack of automatic registration and coordination between the fluoroscopic and 3-dimensional views, the physician is required to switch his or her attention back and forth between the displays and mentally register the different information that they contain.
Some existing methods for registering anatomical images and electro-anatomical maps with 3-dimensionalimages acquired by a different modality generally rely on location data. The mapping catheter is placed at a number of known locations in the organ of interest, such as the heart, and the position coordinates are recorded. These same locations are marked or otherwise recorded in the 3-dimensionalimage. This technique generally requires the operator of the system to take time to find and mark the desired locations for the purpose of registration, in addition to the actions taken as part of the mapping procedure itself.
Various methods are known in the patent literature for automatically registering a fluoroscopic image with a 3-dimensional map. Such methods are described, for example, in commonly assigned U.S. Pat. No. 6,314,310 to Ben-Haim, et al., whose disclosure is incorporated herein by reference.
More recently, a different approach was disclosed in commonly assigned U.S. Patent Application Publication No. 2014/0114173, which is herein incorporated by reference. This document addresses placing a 2-dimensional fluoroscopic image of the thorax in registration with a 3-dimensional map functional electroanatomic map of the heart. A coordinate system registration module includes radiopaque elements arranged in a fixed predetermined pattern and configured, in response to the radiopaque elements generating a fluoroscopic image, to define a position of the module in a fluoroscopic coordinate system of reference. The module further includes one or more connections configured to fixedly connect the module to a magnetic field transmission pad at a predetermined location and orientation with respect to the pad, so as to characterize the position of the registration module in a magnetic coordinate system of reference defined by the magnetic field transmission pad.
One approach to image transformation is proposed in U.S. Pat. No. 8,300,941 to Pilu et al., which involves correcting for perspective distortion by identifying a best grid hypothesis for a surface coded pattern. The method comprises: extracting a set of straight line hypotheses from the coded surface pattern; clustering the straight line hypotheses by orientation; for each cluster, extracting a set of line pencil hypotheses; generating a set of regular grid hypotheses from pairs of the line pencil hypotheses; and determining the best regular grid hypothesis.